爱立信（Ericsson）：2026面向通信系统的可信人工智能白皮书（英文版）（21页）.pdf

1、Ericsson White PaperGFTL-26:000788 UenJune 2026Trustworthy AI for Telecom SystemsTrustworthy AI for Telecom SystemsContentJune 20262ContentAbstract 3Introduction 4Trustworthiness for traditional/generic AI/ML 5Trustworthiness for foundation models and LLMs 8Trustworthiness for agentic AI 10Example u

2、se cases 12Conclusion 16References 17Authors 19Trustworthy AI for Telecom SystemsAbstractJune 20263AbstractArtificial intelligence(AI)is becoming integral to next-generation telecom systems,but it brings risks.The recent AI advancements in large language models(LLMs)and agentic AI introduce new dime

3、nsions to that risk.To trust AI-enabled systems,we must be able to trust AI itself and comply with regulations such as the European Union(EU)AI Act.Trust means ensuring the system works as intended and does no harm.The key message of the paper is that for AI to be integrated into the telecom domain,

4、including 5G and 6G networks,it must move beyond mere performance metrics to a holistic framework of trustworthiness.These capabilities should be embedded by design in the telecom domain.Trustworthiness is a core requirement for adopting AI-based systems,especially in live networks.Trustworthy AI fo

5、r Telecom SystemsIntroduction June 20264Introduction As networks evolve into AI-native architectures,AI moves from a recommended trait to a foundational requirement,embedding trust at the core.In 5G,6G,and autonomous network management,trustworthiness encompasses safety,security,transparency,reliabi

6、lity,and ethics.This integration of AI introduces a complex paradox:while AI is essential for managing the scale and complexity of modern traffic,its black box nature and susceptibility to adversarial manipulation pose risks to safety,transparency,and security.If not addressed,these risks might affe